Get one Trend with its computed time-series points (count + per-intent breakdown per interval bucket). Points are sparse: interval buckets with zero matches are omitted, not stored as 0 — treat missing buckets as zero when charting. Not metered. (requires a free Prowlo account — call it to get a signup link)
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Trend id to fetch (from trend_list) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and idempotentHint annotations, the description discloses sparse data behavior (missing buckets should be treated as zero), notes that the tool is not metered, and mentions the Prowlo account requirement. These are significant behavioral details that aid correct usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient: two sentences plus a parenthetical. It front-loads the primary purpose, then adds essential behavioral notes (sparse points, metering, authentication) without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter get tool with no output schema, the description offers a clear outline of the returned data (count + per-intent breakdown) and sparse points behavior. It does not specify error handling or the full response shape, but it is sufficiently complete for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'id' has full schema coverage with the description 'Trend id to fetch (from trend_list),' so the schema already communicates the parameter's meaning. The tool description adds no further parameter-level semantics, matching the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get one Trend with its computed time-series points,' specifying the resource and the key output. It distinguishes from trend_list by emphasizing a single Trend and its time-series data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through the parameter description ('from trend_list') and the focus on a single Trend, but it does not explicitly name alternative tools or state when to prefer this over trend_list. No clear when-not-to-use guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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